Quasi-linear Sensor Management

Add to your list(s) Download to your calendar using vCal

• Marco Huber (University of Karlsruhe)
• Friday 06 March 2009, 15:00-16:00
• Engineering Department, CBL Room 438.

If you have a question about this talk, please contact Zoubin Ghahramani.

In multimodal sensor systems, such as sensor networks, the main objective of sensor management is to utilize sensors and their sensing modalities in a most informative way. This requires planning decisions over multiple time steps. For computationally constrained sensor systems, the “quasi-linear sensor management” approach allows efficient and meaningful decision making for nonlinear non-Gaussian systems by utilizing open-loop feedback control. In this talk, three key techniques of the quasi-linear sensor management approach are presented: (1) predictive statistical linearization for converting nonlinear non-Gaussian sensor management problems into linear Gaussian ones, (2) optimal branch-and-bound pruning for quickly solving linear Gaussian sensor management problems, and (3) Gaussian mixture reduction for bounding the growth of the number of mixture components when employing Gaussian mixture models for Bayesian filtering. The effectiveness of these techniques is demonstrated by means of simulations including mobile sensor control and sensor scheduling in sensor networks.

This talk is part of the Machine Learning @ CUED series.

This talk is included in these lists:

• Seminar
• All Talks (aka the CURE list)
• Biology
• CBL important
• Cambridge Centre for Data-Driven Discovery (C2D3)
• Cambridge Forum of Science and Humanities
• Cambridge Language Sciences
• Cambridge Neuroscience Seminars
• Cambridge talks
• Chris Davis' list
• Creating transparent intact animal organs for high-resolution 3D deep-tissue imaging
• Engineering Department, CBL Room 438
• Featured lists
• Guy Emerson's list
• Hanchen DaDaDash
• Inference Group Summary
• Information Engineering Division seminar list
• Interested Talks
• Joint Machine Learning Seminars
• Life Science
• Life Sciences
• ML
• Machine Learning @ CUED
• Machine Learning Summary
• Neuroscience
• Neuroscience Seminars
• Neuroscience Seminars
• Required lists for MLG
• Simon Baker's List
• Stem Cells & Regenerative Medicine
• Trust & Technology Initiative - interesting events
• bld31
• dh539
• kt532's list
• ndk22's list
• ob366-ai4er
• rp587
• yk373's list

Note that ex-directory lists are not shown.